[quickthrower2]

Been thinking about this. My naive way to do this using existing LLMs is to have a JSON the LLM can spit out when it wants to store and then then calling code shoves that in a “RAG” DB. It also has the ability to generate queries if it’s knowledge.

[pacjam]

This is similar to how our external context is implemented under the hood - you might be interested in our perpetual chat bot example in the GitHub repo (https://github.com/cpacker/MemGPT), the message traces in the demo GIF should give you an idea of how things work at a glance.